Sample Size Calculations Based on Generalized Estimating Equations for Population Pharmacokinetic Experiments

ABSTRACT

We present a method for calculating the sample size of a pharmacokinetic study analyzed using a mixed effects model within a hypothesis testing framework. A sample size calculation method for repeated measurement data analyzed using generalized estimating equations has been modified for nonlinear models. The Wald test is used for hypothesis testing of pharmacokinetic parameters. A marginal model for the population pharmacokinetic is obtained by linearizing the structural model around the subject specific random effects. The proposed method is general in that it allows unequal allocation of subjects to the groups and accounts for situations where different blood sampling schedules are required in different groups of patients. The proposed method has been assessed using Monte Carlo simulations under a range of scenarios. NONMEM was used for simulations and data analysis and the results showed good agreement.

Key Words:

• GEE
• Mixed effects modeling
• Nonlinear models
• Pharmacokinetics
• Power
• Sample size

ACKNOWLEDGMENTS

This work formed part of the Ph.D. thesis of Kayode Ogungbenro, who was sponsored by the University of Manchester (through the OSS award) and the Centre for Applied Pharmacokinetic Research (CAPKR is funded by a consortium of pharmaceutical companies, including Eli Lilly, GlaxoSmithKline, Novartis, Pfizer, and Servier).

Notes

∗set to 0.05.

∗set to 0.05.